1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Foundation Model for Music Informatics
Minz Won, Yun-Ning Hung, Duc Le
This paper investigates foundation models tailored for music informatics, a domain currently challenged by the scarcity of labeled data and generalization issues. To this end, we c…
Scaling Up Music Information Retrieval Training with Semi-Supervised Learning
Yun-Ning Hung, Ju-Chiang Wang, Minz Won +1
In the era of data-driven Music Information Retrieval (MIR), the scarcity of labeled data has been one of the major concerns to the success of an MIR task. In this work, we leverag…
Music Source Separation with Band-Split RoPE Transformer
Wei-Tsung Lu, Ju-Chiang Wang, Qiuqiang Kong +1
Music source separation (MSS) aims to separate a music recording into multiple musically distinct stems, such as vocals, bass, drums, and more. Recently, deep learning approaches s…
Jointist: Simultaneous Improvement of Multi-instrument Transcription and Music Source Separation via Joint Training
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…